{"id":259662,"date":"2025-02-19T16:00:14","date_gmt":"2025-02-19T16:00:14","guid":{"rendered":"https:\/\/userpilot.com\/blog\/?post_type=pitt&p=259662"},"modified":"2025-12-02T13:04:43","modified_gmt":"2025-12-02T13:04:43","slug":"analytics-setups-timo-dechau","status":"publish","type":"pitt","link":"https:\/\/userpilot.com\/blog\/pitt\/analytics-setups-timo-dechau\/","title":{"rendered":"Measure Your Product Strategy – A New Learning for Analytics Setups"},"content":{"rendered":"

I decided to take on an interesting challenge: creating tracking plans for common startup tools. I chose these tools because people are generally familiar with them, and they cover different product directions. This means if your product overlaps with any of these tools (like Notion), you can find useful inspiration.<\/p>\n

My process for creating these tracking plans<\/a> was simple. Each morning, I’d set up my recording, open the tool’s website, and think through the core use cases I wanted to focus on. Then, I’d create a first draft and iterate from there.<\/p>\n

I chose this approach because I wanted to give real insights into my thought process and design decisions when building analytics setups. Sure, I could show you hundreds of examples of initial analytics setups – which events to track, how to structure properties – but that would miss the interesting part: the decision-making process.<\/p>\n

We’re talking about design here, not math. There’s rarely a clear right or wrong answer, it’s about balancing tradeoffs and making thoughtful choices.<\/p>\n

Creating tracking plans for Notion, Slack, Asana, Superhuman, and Vimcal led me to develop a two-bucket approach to analytics setups:<\/p>\n

    \n
  1. Core functionality:<\/b> Cover how people actually use the product.<\/li>\n
  2. Strategic direction: <\/b>Track metrics that reflect the product’s strategic goals and unique value proposition.<\/li>\n<\/ol>\n
    \"Two
    Two-bucket approach to analytics setups.<\/figcaption><\/figure>\n

    <\/p>\n